The goal of the research project is to carry out an extensive investigation of several areas of statistical methodology for the design and analysis of biomedical studies, planned or observational, applicable to various areas of health research including cancer, toxicology, environmental health and epidemiology. The objective is to provide more efficient statistical methods to achieve valid conclusions at less cost in terms of time and sample size. The research falls into four main categories: (a) Interim monitoring of clinica trials; (b) Design and analysis of long-term animal tumorigenicity bioassays; (c) Quality control procedures for laboratory tests; (d) General statistical methods for survival data. Specific projects include the use of repeated confidence intervals to monitor quantities of interest such as hazard ratios, odds ratio or median response time in follow-up studies. An important advantage of this approach is that its flexibility allows inferences to be drawn independent from any stopping rule. It is planned to investigate the design of efficient and robust interim sacrificing schedules in long-term animal studies. Statistical methods for describing association among incidence of distinct diseases from pathology data gathered from these experiments will also be studied. The existence of negative correlations, not demonstrable as spurious, could have serious implications concerning the definition of a "carcinogen." Under the last category (d) several projects are planned, including development of methodology to analyze discrete time survival data with covariates and multiple end-points which can arise, for example, in a skin cancer study.